Low muscle strength thresholds for the detection of cardiometabolic risk in adolescents

Mark D. Peterson, Peng Zhang, William A. Saltarelli, Paul S. Visich, Paul M. Gordon

Research output: Contribution to journalArticlepeer-review

55 Scopus citations


Introduction There is an association between strength and health among adolescents, yet, what remains to be determined is sex-specific cut points for low strength in the detection of risk in this population. The purpose of this study was to determine thresholds of low grip strength in a large cohort (N=1,326) of adolescents. Methods All data were collected between 2005 and 2008, and analyzed in 2014-2015. A cardiometabolic risk score (MetScore) was computed from the following components: percent body fat, fasting glucose, blood pressure, plasma triglyceride levels, and high-density lipoprotein cholesterol. A high-risk cardiometabolic phenotype was characterized as ≥75th percentile of the MetScore. Conditional inference tree analyses were used to identify sex-specific, low normalized strength (grip strength/body mass) thresholds and risk categories. Results Lower strength was independently associated with increased odds of the high-risk cardiometabolic phenotype, such that for every 5% decrement of normalized strength, there were 1.48 and 1.45 increased odds (p<0.001) for boys and girls, even after adjusting for cardiorespiratory fitness and physical activity. Conditional tree analysis revealed a high-risk threshold for boys (≤0.33) and girls (≤0.28), as well as an intermediate threshold (boys, >0.33 and ≤0.45; girls, >0.28 and ≤0.36). Conclusions These sex-specific thresholds of low strength can be incorporated into a clinical setting for identifying adolescents that would benefit from lifestyle interventions to improve muscular fitness and reduce cardiometabolic risk.

Original languageEnglish
Pages (from-to)593-599
Number of pages7
JournalAmerican Journal of Preventive Medicine
Issue number5
StatePublished - May 1 2016


Dive into the research topics of 'Low muscle strength thresholds for the detection of cardiometabolic risk in adolescents'. Together they form a unique fingerprint.

Cite this